Metabolomic-transcriptomic landscape of 8-epidiosbulbin E acetate -a major diterpenoid lactone from Dioscorea bulbifera tuber induces hepatotoxicity

Journal Pre-proof Metabolomic-transcriptomic landscape of 8-epidiosbulbin E acetate -a major diterpenoid lactone from Dioscorea bulbifera tuber induces hepatotoxicity Wei Shi, Yan Jiang, Dong-Sheng Zhao, Li-Long Jiang, Feng-Jie Liu, Zi-Tian Wu, Zhuo-Qing Li, Ling-Li Wang, Jing Zhou, Ping Li, Hui-Jun Li PII:

S0278-6915(19)30677-5

DOI:

https://doi.org/10.1016/j.fct.2019.110887

Reference:

FCT 110887

To appear in:

Food and Chemical Toxicology

Received Date: 9 April 2019 Revised Date:

8 October 2019

Accepted Date: 12 October 2019

Please cite this article as: Shi, W., Jiang, Y., Zhao, D.-S., Jiang, L.-L., Liu, F.-J., Wu, Z.-T., Li, Z.-Q., Wang, L.-L., Zhou, J., Li, P., Li, H.-J., Metabolomic-transcriptomic landscape of 8-epidiosbulbin E acetate -a major diterpenoid lactone from Dioscorea bulbifera tuber induces hepatotoxicity, Food and Chemical Toxicology (2019), doi: https://doi.org/10.1016/j.fct.2019.110887. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

1

Metabolomic-transcriptomic landscape of 8-epidiosbulbin E acetate

2

-a major diterpenoid lactone from Dioscorea bulbifera tuber induces

3

hepatotoxicity

4 a

b,*

a

a

a

5

Wei Shi , Yan Jiang , Dong-Sheng Zhao , Li-Long Jiang , Feng-Jie Liu , Zi-Tian

6

Wu , Zhuo-Qing Li , Ling-Li Wang , Jing Zhou , Ping Li , Hui-Jun Li

a

a

a

a

a

a,*

7 8 9 10

a

State Key Laboratory of Natural Medicines, China Pharmaceutical University,

Nanjing, 210009, China b

Nanjing Forestry University, Nanjing, 210037, China

11 12

*Corresponding Authors:

13

Hui-Jun Li, PhD

14

State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 24

15

Tongjia Lane, Nanjing 210009, China.

16

E-mail: [email protected].

17

Tel.: +86 25 83271382; Fax: +86 25 83271379.

18

Yan Jiang, PhD

19

Nanjing Forestry University, No. 159 Longpan Road, Nanjing 210037, China.

20

E-mail: [email protected].

21

Tel.: +86 25 83271382; Fax: +86 25 83271379.

22 1

23

ABSTRACT

24

Studies have shown that 8-epidiosbulbin E acetate (EEA), a major diterpenoid lactone

25

in the tuber of Dioscorea bulbifera, can induce hepatotoxicity in vivo. However, the

26

underlying mechanisms remain unknown. Using the integrated transcriptomic and

27

metabolomics method, in this study we investigated the global effect of EEA exposure

28

on the transcriptomic and metabolomic profiles in mice. The abundance of 7131

29

genes and 42 metabolites in the liver, as well as 43 metabolites in the serum were

30

altered. It should be noted that EEA mainly damaged hepatic cells through the

31

aberrant regulation of multiple systems primarily including bile acid metabolism, and

32

taurine and hypotaurine metabolism. In addition, an imbalance of bile acid

33

metabolism was found to play a key pat in response to EEA-triggered hepatotoxicity.

34

In summary, these findings contributed to understanding the underlying mechanisms

35

of EEA hepatotoxicity.

36 37

Keywords: 8-Epidiosbulbin E acetate; Transcriptomics; Metabolomics; Hepatoto

38

xicity; Bile acid metabolism

2

39

1. Introduction

40

Dioscorea bulbifera tuber (DBT), a medicinal herb belonging to the

41

Dioscoreaceae family, has been widely used in China and exhibits a variety of

42

pharmacological activities, including goiter inhibitory, anti-inflammatory, and

43

antitumor effects (Tang, 1995; Rao et al., 2010; Liu et al., 2011; Wang et al., 2012).

44

Despite a wide array of therapeutic values, the hepatotoxicity of DBT has been a

45

critical safety issue restricting its application (Liu, 2002; Huang et al., 2013). Liver

46

injury cases have frequently been found to be associated with the consumption of

47

DBT in clinical practice (Yang et al., 2006; Lu and Wu, 2014). Studies have attributed

48

the DBT-induced hepatotoxicity to different causes, including oxidative damage to

49

hepatic mitochondria or bile acid (BA) metabolic disorders (Wang et al., 2010; Wang

50

et al., 2011; Zhao et al., 2017; Xiong et al., 2017).

51

A number of diterpenoid lactones (DLs) have been isolated and identified from

52

DBT; the major DLs found in DBT were reportedly 8-epidiosbulbin E acetate (EEA)

53

and diosbulbin B (DIOB) (Kawasaki et al., 1968; Murray et al., 1984; Gao et al.,

54

2002). Our preliminary study revealed that DIOB and EEA played an important role

55

in the hepatotoxicity of DBT (Shi et al., 2018). However, compared with abundant

56

investigations on DIOB, few studies have been associated with EEA. Lin et al.

57

demonstrated that administration of EEA could cause severe acute hepatotoxicity in

58

vivo and the observed liver injury required cytochromes P450-mediated metabolism

59

(Lin et al., 2015). The electrophilic intermediate generated by metabolic activation of

60

the furan ring is responsible for EEA-induced hepatotoxicity (Lin et al., 2016). 3

61

Furthermore, the cysteine- and lysine-based protein adduction with the reactive

62

intermediate was found both in vitro and in vivo, where the changes in levels of the

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protein adductions might be related to alternations in degrees of EEA-induced

64

hepatotoxicity (Lin et al., 2016). Although these investigations facilitate a better

65

understanding of the mechanism of hepatoxic action of EEA, a consensus is still far

66

from being realized. Therefore, it is urgently necessary to reveal the underlying

67

mechanism of EEA-induced hepatic damage.

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Generating high-throughput data from multiple technique platforms, systems

69

biology is being increasingly applied for the search of novel biomarkers and a deeper

70

understanding of the toxic effects of xenobiotics (Hua et al., 2015; Basu et al., 2017).

71

Transcriptomics, which can identify sensitive and detailed insights into the potential

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mechanisms of toxic action at an earlier molecular level, provides a valuable platform

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in predicting possible toxicity and further revealing the potential biomarkers in

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toxicity (Cui et al., 2010; Li et al., 2014). Focusing on studying the multi-parametric

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metabolic responses in living systems after pathophysiological stimuli or genetic

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modification, metabonomics can also relate these responses to the gene expression

77

profiles and pathology results (Chen et al., 2018; Fan et al., 2016). Moreover, the

78

integration of transcriptomics and metabolomics profiles may offer a greater

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reliability in expounding metabolic alterations and allow further elucidation toward

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the toxic effects and mechanism (Lu et al., 2013). To the best of our knowledge, the

81

integrated application of these two platforms to characterize EEA-induced hepatic

82

toxicity has not yet been reported. 4

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EEA has a potential hepatotoxic effect on the physiological and biological

84

functions of organisms via regulating multiple metabolic pathways to an abnormal

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state. In the present study, an integrated analysis of general toxicity studies,

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transcriptomics, and metabonomics approaches was applied to investigate

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EEA-induced hepatotoxicity in mice (Fig. 1). Moreover, the pathways related to the

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toxic effects of EEA were summarized by correlation network analysis and validated

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by quantitative real-time PCR (qRT-PCR) and Western blot analyses. The objectives

90

of the present study were to provide a comprehensive insight into the mechanism and

91

potential biomarkers of EEA-induced hepatotoxicity.

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2. Materials and methods

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2.1. Reagents

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The DBT was obtained from Yunnan province, China. The sample was

96

authenticated by Prof. Hui-Jun Li and deposited at State Key Laboratory of Natural

97

Medicines (China Pharmaceutical University, Nanjing, China).

98

Chromatographic grade methanol was obtained from CNW Technologies Gmbh

99

(Dussel-dorf, Germany). Chloroform and pyridine were provided by Adamas Reagent

100

Co., Ltd. (Basel, Switzerland). L-2-Chlorophenylalanine (internal standard, IS) was

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purchased from Shanghai Heng Bo Biological Technology Co., Ltd. (Shanghai,

102

China).

103

trimethylchlorosilane (TMCS) was purchased from REGIS Technologies (Chicago,

N,O-bis

(trimethylsilyl)

trifluoroacetamide

5

(BSTFA)

with

1%

104

USA). Deionized water (18 MΩ cm) was prepared by distilled water through a

105

Milli-Q system (Massachusetts, USA). Bile acid standards were purchased from

106

Sigma-Aldrich Co. (St. Louis, MO, USA), including cholic acid (CA), lithocholic

107

acid (LCA), deoxycholic acid (DCA), ursodeoxycholic acid (UDCA), hyodeoxycholic

108

acid

109

glycochenodeoxycholic acid (GCDCA), tauroursodeoxycholic acid (TUDCA),

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taurohyodeoxycholic acid (THDCA), taurocholic acid (TCA), taurolithocholic acid

111

(TLCA), dehydrocholic acid (DHCA, IS). EEA was isolated from DBT in our

112

laboratory and the chemical structure (Fig. S1) was confirmed by extensive

113

spectroscopic analyses. The purity of EEA was > 98%, detected by ultra-high

114

performance liquid chromatography (UPLC) using peak area normalization method.

115

Other reagents and solvents were of analytical grade.

116

2.2. Animals and treatment

(HDCA),

chenodeoxycholic

acid

(CDCA),

glycocholic

acid

(GCA),

117

Male ICR mice (4–5 weeks old; weighing: 18–22 g) were purchased from

118

Sino-British SIPPR/BK Lab Animal Ltd. (Shanghai, China). Mice were fed a standard

119

laboratory diet and given free access to tap water. They were kept in a controlled

120

room temperature (22 ± 2oC), humidity (60 ± 5%), and a 12 h dark/light cycle for at

121

least 7 days before treatment. All animal studies were performed according to the

122

Provision and General Recommendation of Chinese Experimental Animals

123

Administration Legislation and were approved by Department of Science and

124

Technology of Jiangsu Province (license number: SYXK (SU) 2016-0011).

125

The mice were orally administered EEA (150 mg/kg, suspended in 0.5% 6

126

CMC-Na, n = 10) for 36 h, and 0.5% sodium carboxymethyl cellulose (CMC-Na) was

127

used as a vehicle control (n = 10). During the time they were fasted from food, but no

128

water 12 h prior to the administration of the test suspension. Blood samples and liver

129

tissues were collected at 36 h following treatment. All biological samples were

130

lyophilized and stored at −80oC before further analysis.

131

In a separate study, mice were given EEA at 30 mg/kg (i.g.), blood and liver were

132

collected 36 h after the administration, and the serum alanine aminotransferase (ALT),

133

aspartate aminotransferase (AST), total bilirubin (TBIL), direct bilirubin (DBIL) and

134

alkaline phosphatase (ALP) levels were measured. Liver samples were collected and

135

prepared for further western blots analysis.

136

2.3. Detection of AST, ALT, TBIL, DBIL and ALP levels from serum

137

Blood was collected from the eyeball and centrifuged at 1500g for 10 min at 4oC.

138

Serum AST, ALT, TBIL, DBIL and ALP activities were measured on Cobas 8000

139

modular analyzer (Basel, Switzerland).

140

2.4. Histopathologic examination

141

Liver tissues were fixed in 10% neutral buffered formalin, paraffin processed,

142

and sectioned at 4 µm. For histological evaluation, the tissue sections were stained

143

with hematoxylin and eosin (H&E) and examined for histopathological changes under

144

the Olympus DX45 microscope (Tokyo, Japan).

145

2.5. RNA isolation, cDNA library construction and illumina deep sequencing

146

Six liver tissue samples from three biological replicates of the vehicle and 7

147

EEA-treated mice groups were used for the transcriptomic analysis. Total RNA was

148

extracted using Trizol reagent (Invitrogen, USA) according to the manufacturer’s

149

protocol. The RNA integrity was assessed using a Bioanalyzer 2100 system (Agilent

150

Technologies, USA). The RNA samples for the transcriptome analysis were prepared

151

using an Illumina kit, following the manufacturer’s recommendations. The fragments

152

were purified via agarose gel electrophoresis and enriched by PCR amplification to

153

create a cDNA library. Sequencing and data processing (including the statistical

154

analysis and selection of differentially expressed genes) were all performed following

155

the methods (Katz et al., 2010).

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2.6. Metabolic profiling analysis

157

An aliquot of 100 µL of serum or 60 mg of liver tissue sample was placed in a 2

158

mL eppendorf (EP) tube, followed by extraction with 0.48 mL of mixture of

159

chloroform and methanol (Vmethanol : Vchloroform = 3:1). Afterwards, 20 µL of

160

L-2-chlorophenylalanine (1 mg/mL stock in dH2O) were added as internal standard,

161

and samples were vortex-mixed for 30 s. A ball mill was used to homogenize the

162

samples for 4min at 45 Hz, followed by sonication for 5 min, and then centrifugation

163

for 15 min at 28000g, 4oC. Quality control (QC) samples were prepared by pooling

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aliquots of all samples and were processed with the same procedure as that followed

165

for the experiment samples. The extracts were dried in a vacuum concentrator at 30oC

166

for approximately 1.5 h, and then 60 µL of methoxyamine hydrochloride in pyridine

167

(20 mg/mL) was added to the residue, being derivatized at 80°C for 30 min.

168

Subsequently, 80 µL of the BSTFA regent (1% TMCS, v/v) were added into the 8

169

sample aliquots, incubated for 1.5 h at 70oC, and 10 µL FAMEs (Standard mixture of

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fatty acid methyl esters, C8-C16:1 mg/mL; C18-C24:0.5 mg/mL in chloroform) was

171

added to the samples until cooling to the room temperature. The pooled QC sample

172

was injected five times at the beginning of the run in order to ensure system

173

equilibration and then every 10 samples to further monitor the stability of the analysis.

174

2.7. GC-TOF MS analysis

175

GC-TOF MS analysis was performed using an Agilent 7890 gas chromatograph

176

system (Agilent Technologies Inc., Santa Clara, California, USA) coupled with a

177

Pegasus HT time-of-flight mass spectrometer (LECO Corp., St. Joseph, MI, USA)

178

that included an Rxi-5Sil MS column (Restek, Bellefonte, USA), which was 30 m in

179

length and 0.25 mm in inner diameter with a film thickness of 0.25 µm. A 1 µL aliquot

180

of the analyte was injected in splitless mode. The carrier gas was helium with a 3

181

mL/min front inlet purge flow and a constant 1 mL/min gas flow rate through the

182

column. The initial temperature was maintained at 50°C for 1 min, raised to 310°C at

183

a rate of 10°C/min, and then kept for 5 min at 310°C. The injection, transfer line and

184

ion source temperatures were 280, 270, and 220°C, respectively. The energy was -70

185

eV in electron impact mode. The mass spectrometry data were acquired in full-scan

186

mode with the m/z range of 50 − 500 at a rate of 20 spectra per second after a solvent

187

delay of 370 s.

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LECO Chroma TOF4.3X software and LECO-Fiehn Rtx5 database (Leco Corp.,

189

St. Joseph, MI, USA) were used for the raw data acquisition and processing, such as

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the raw peak exacting, raw peak exacting, data baseline filtering and calibration, peak 9

191

alignment, deconvolution analysis, peak identification, and peak area integration. The

192

retention time index method was used for peak identification, with a tolerance value

193

of 5000.

194

Principal

component

analysis

(PCA)

and

orthogonal

partial

195

least-squares-discriminate analysis (OPLS-DA) were performed using SIMCA

196

version

197

(http://www.metaboanalyst.ca/). Statistical analyses were conducted by SPSS

198

software version 19.0 (IBM Corp., Armonk, USA). On the basis of variable

199

importance in the projection (VIP) scores > 1.0 obtained from the OPLS-DA model

200

and p values < 0.05 evaluated by the student’s t-test, a set of discriminating

201

metabolites were determined (Afanador et al., 2013; Matthews et al., 1985). Heat

202

maps and hierarchical cluster analyses were conducted using MeV 4.6.0 software. The

203

pathway mapping of the serum was analyzed with MetScape 3 (Karnovsky et al.,

204

2011).

205

2.8. Integrated pathway analysis

14.0.1

(Umetrics,

Sweden)

and

MetaboAnalyst

4.0

206

To identify the related pathways among the metabolites and genes,

207

MetaboAnalyst 4.0 (http://www.metaboanalyst.ca/) was utilized to further holistic

208

pathway analysis. Hypergeometric tests were calculated to evaluate the enrichment

209

analysis between metabolome and transcriptome data, and the topology analysis

210

(Degree Centrality) were applied to evaluate whether a given gene or metabolite plays

211

an important role in a biological response based on its position in the pathway (Chong

212

et al., 2018). 10

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2.9. Real-time RT-PCR

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To examine the accuracy and reproducibility of the Illumina RNA-Seq results,

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qRT-PCR assays were performed with gene-specific primers (Suo et al., 2018). Total

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RNA was extracted from EEA-treated mice using the TRIzol reagent (Invirtrogen,

217

USA) and qRT-PCR was performed using SYBR Premix Ex Taq II (TaKaRa, Japan)

218

following the manufacturer’s protocol. qRT-PCR was conducted on Applied

219

Biosystems 7,300 machine (Carlsbad, USA) as follows: 3 min at 95°C for

220

denaturation, followed by 40 cycles of 7 s at 95°C for denaturation, 10 s at 57°C for

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annealing, and 30 s at 72°C for extension. For each target gene, triplicate reactions

222

were performed. Relative gene expression levels were calculated from cycle threshold

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values using the 2−∆∆Ct method (Livak and Schmittgen, 2001). The sequences of

224

specific primers used for qRT-PCR are listed in Table 1.

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2.10. Western blotting assay

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Western blot analysis was performed as previously described with minor

227

modifications (Renaud et al., 2011). Liver homogenates were prepared in radio

228

immunoprecipitation assay (RIPA) buffer. Protein concentrations were determined

229

using bicinchonininc acid (BCA) assay method according to the manufacturer's

230

instructions (Beyotime, China). Samples were subjected to polyacrylamide gel

231

electrophoresis, transferred onto a polyvinylidene difluoride membrane, and probed

232

with the respective primary and secondary antibodies. Membranes were stripped and

233

reprobed with a β-actin antibody as the loading control. Proteins were detected using

11

234

chemiluminescence.

235

2.11. UPLC-QqQ-MS profiling and MS conditions for BAs analysis

236

Metabolomic profiling analysis of BAs was performed by following our

237

previously published method (Zhao et al., 2017). Liver samples (60 mg) were mixed

238

with 400 µL of methanol containing 10 µL IS. The mixture was vortexed for 5 min,

239

followed by centrifugation at 28000g for 10 min at 4°C, and the supernatant was

240

analyzed by UPLC-QqQ/MS.

241

3. Results

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3.1. Hepatotoxicity of EEA in mice

243

Histopathologic analysis (n = 5 per group) showed inflammatory cell infiltration,

244

hepatic cell necrosis and focal necrosis (Fig. 2A, B) in mice liver i.g. administered

245

EEA at 150 mg/kg. Additionally, the serum ALT/AST/TBIL/DBIL levels significantly

246

increased (p <0.01), compared with 30.1 ± 4.4 U/L (ALT), 105.0 ± 27.3 U/L (AST),

247

1.1 ± 0.2 U/L (TBIL) and 0.9 ± 0.2 U/L (DBIL) in mice treated with vehicle (Fig.

248

2C-F). Additionally, the serum ALP levels were also significantly increased (p <0.05)

249

(Fig. 2G). Compared with mice treated with EEA (150 mg/kg), no changes were

250

observed in the levels of ALT/AST/TBIL/DBIL/ALP in mice administered EEA (30

251

mg/kg) (Fig. 2C-G). These findings indicated that EEA administered to the mice at

252

the dose of 150 mg/kg caused potential hepatotoxicity.

253

3.2. Differentially expressed genes (DEGs) identification and selection

12

254

In order to identify hepatotoxicity-related candidate genes that responded to EEA

255

(150 mg/kg) infection, four transcriptome profiles were performed. First, the

256

expression level of each gene was normalized using the fragments per kilobase of

257

transcript per million mapped reads (FPKM) (Trapnell et al., 2010). The genes with

258

data false discovery rate (FDR) < 0.001 and estimated absolute log2fold change

259

(log2FC) ≥ 1 in sequence counts across libraries were then considered as significant

260

DEGs. Finally, a total of 7131 DEGs were identified between EEA-treated groups and

261

the control groups. Of these genes, 3749 genes were up-regulated and 3382 genes

262

were down-regulated in the liver of mice given EEA at 150 mg/kg.

263

3.3. Gene annotation and the functional classification of DEGs

264

To gain additional insights into the function of DEGs, GO and KEGG databases

265

were used to annotate and classify DEG functions. DEGs overrepresented in the two

266

groups using GO analysis (Fig. S3) suggested that the cofactor metabolic process was

267

the most significantly enriched biological function.

268

The KEGG database was used to further understand the biological functions and

269

pathways of DEGs. Based on the KEGG pathways enrichment analysis, metabolic

270

pathways were found to be one of the most over-represented processes in mice

271

exposed to EEA treatment (150 mg/kg), suggesting that enzymatic reaction and

272

enzymes might play key roles in the development of EEA-induced liver injury. The

273

list of over-represented KEGG pathways in mice exposed to EEA (150 mg/kg) is

274

presented in Table S1.

13

275

3.4. Metabolic profiling analysis of serum and livers

276

The stability and repeatability of the GC-TOF MS system for large-scale sample

277

analysis were confirmed by the analysis of pooled QC samples and the retention time

278

of the internal standard. The serum and liver metabolic profiling analysis was

279

performed according to the proposed approach (Dunn et al., 2011). Typical total ion

280

chromatograms (TICs) of serum and livers samples from the control and EEA (150

281

mg/kg) groups are presented in Fig. S4 (A: serum; B: livers). A total of 562 and 722

282

metabolite peaks in serum and livers were respectively extracted through GC-TOF

283

MS (Fig. S5). To obtain a comprehensive view of the metabonome, PCA was

284

performed to visualize the trends and outliers in the data for the control and EEA (150

285

mg/kg) groups. The RSDs of the retention time of L-2-chlorophenylalanine (IS) in

286

serum and livers were 0.0048% and 0.0132%, respectively. The PCA also showed a

287

tight grouping of the QC samples (Fig. 3A and Fig. 4A). These data demonstrate a

288

high reproducibility of the method. The score plots revealed that there were no

289

outliers and that the two groups were clearly separated (Fig. 3 and Fig. 4).

290

To study the changes in metabolites in mice after EEA (150 mg/kg)

291

administration, the liver and serum samples were analyzed by OPLS-DA to identify

292

the variables responsible for the differences among groups (Bylesjö et al., 2010; Chan

293

et al., 2009). In the OPLS-DA score plots (Fig. 3B and Fig. 4B), the EEA groups

294

exhibited a tendency to deviate from the control groups, revealing a visible

295

perturbation of the metabolic profiles in EEA-150 mg/kg treated groups. The models

296

were validated by the permutation test. The R2 values of serum and liver samples in 14

297

the OPLS-DA models were 0.879 and 0.755 (Fig. 3C and Fig. 4C), respectively,

298

indicating an excellent prediction.

299

To identify the variables responsible for this large separation, the importance of

300

the VIP statistics from OPLS-DA modelling and t-tests (P< 0.05) between the two

301

groups was used to pre-select variables. The GC-TOF MS spectra of the metabolites

302

were analyzed based on mass spectra libraries, and the metabolites had to meet the

303

conditions VIP > 1 and P < 0.05. In the EEA-treated groups (150 mg/kg), a total of 43

304

and 42 metabolites were, respectively, identified in the serum and liver samples (Table

305

S2). Additionally, heat maps were created based on the average fold change of each

306

metabolite to intuitively evaluate the variation tendency of the metabolite

307

concentrations between the control and EEA (150 mg/kg)-treated groups. As shown in

308

Fig.5, 6 metabolites had decreased in the serum and 7 metabolites had increased in the

309

livers. Compared with the control group, one metabolite (3-hydroxybutyric acid) was

310

decreased, while six metabolites (2-hydroxybutanoic acid, uracil, N-methyl-dl-alanine,

311

fumaric acid, L-malic acid and citric acid) had an opposite tendency in both serum

312

and livers. Subsequently, the metabolic pathways analysis was performed based on

313

the metabolites in serum and livers. As a web-based server supporting pathway

314

analysis, MetaboAnalyst 4.0 (www.metaboanalyst.ca) integrates enrichment analysis

315

and pathway topology analysis to discover the significant and relevant pathways

316

affected by EEA administration. Three metabolic pathways (valine, leucine and

317

isoleucine biosynthesis phenylalanine, tyrosine and tryptophan biosynthesis and

318

D-Glutamine and D-glutamate metabolism) participated in the most relevant 15

319

pathways affected by EEA, with an impact value of 1.0 in serum (Fig. 6A). Figure 6B

320

demonstrates that elevated phenylalanine, tyrosine and tryptophan biosynthesis was

321

filtered out as significant metabolic pathways marking the impact of EEA in livers.

322

Moreover, compared with the control group, several other important pathways,

323

including citrate cycle (TCA cycle), phenylalanine metabolism, β-alanine metabolism

324

and taurine and hypotaurine metabolism, were activated in both serum and livers. In

325

the present study, our results illustrated that the pathways of EEA-induced

326

hepatotoxicity were related to purine metabolism, glutathione metabolism, as well as

327

primary bile acid biosynthesis in serum or livers of mice treated with EEA at 150

328

mg/kg.

329

3.5. Key pathways related to EEA-induced hepatotoxicity

330

MetaboAnalyst 4.0 was used to visualize and interpret the metabolomic and gene

331

expression profiling data in livers (Chong et al., 2010), allowing us to build and

332

analyze networks of genes and compounds, identify enriched pathways from the

333

differential expression profiling data, and visualize changes in metabolite data.

334

Results indicate that 79 signaling pathways played important roles in EEA-induced

335

liver injury, and the most important 20 pathways in mice exposed to EEA (150 mg/kg)

336

are shown in Fig.7. Amino acid metabolism (valine, leucine and isoleucine

337

degradation, arginine and proline metabolism, tryptophan metabolism, D-glutamine

338

and D-glutamate metabolism, glutathione metabolism and taurine and hypotaurine

339

metabolism), fatty acid metabolism (fatty acid metabolism, primary bile acid

340

biosynthesis and arachidonic acid metabolism), carbohydrate metabolism (TCA cycle, 16

341

propanoate metabolism, pentose and glucuronate interconversions, ascorbate and

342

aldarate metabolism, galactose metabolism and glyoxylate and dicarboxylate

343

metabolism)

344

metabolism-cytochrome P450, metabolism of xenobiotics by cytochrome P450 and

345

drug metabolism-other enzymes) were found to play important roles in EEA-induced

346

hepatotoxicity. Other pathways were involved in metabolism of cofactors, vitamins

347

and nucleotide metabolism, including “retinol metabolism,” “purine metabolism,” and

348

“pyrimidine metabolism.”

349

3.6. Validation of RNA-Seq data by qRT-PCR

and

xenobiotics

biodegradation

and

metabolism

(drug

350

To validate the RNA-Seq data, 10 differentially expressed genes were chosen for

351

a gene expression analysis via qRT-PCR (Fig.S6). In total, these 10 genes exhibited

352

consistent expression patterns between the RNA-Seq data and qRT-PCR. As

353

mentioned above, both data sets strongly correlated in the present study.

354

3.7. Regulation of FN1, UGT1a1, CYP1B1, CYP1A1, CYP2E1, CYP8B1, CYP7A1,

355

BAAT, NTCP, BSEP and MRP3 protein expression in the livers of mice treated with

356

EEA

357

The integrated analysis of the results from transcriptome and metabolome

358

profiles indicated that down-regulation of key enzymes and disorder of BA

359

metabolism in the liver played a pivotal role in the hepatotoxicity of EEA. The results

360

showed downregulation of CYP7A1 and CYP8B1 protein expression in livers from

361

EEA(150 mg/kg)-treated mice compared to vehicle groups. In addition, three 17

362

important BA transporters - NTCP, MRP3, and BSEP protein expression - were also

363

measured with a significant down-regulation of NTCP, MRP3, and BSEP protein

364

expression observed between the control and treatment groups (150 mg/kg).

365

Additionally, CYP1A1 was found to be significantly up-regulated in EEA-treated

366

mice livers. Western blot results are shown in Fig.8A.

367

As shown in Fig. 8B, no significant changes were observed in the levels of

368

CYP7A1, CYP1A1, NTCP and BSEP protein expression in EEA (30 mg/kg) groups,

369

which were in accordance with the results of biochemical indices serum

370

determination.

371

3.8. Quantitative analysis of BAs

372

By combining metabolomics and transcriptomics data, studying the alternation in

373

the BA metabolism pathway after EEA (150 mg/kg) treatment has become an

374

interesting topic. Therefore, concentrations of 12 individual bile acids - including 6

375

free bile acids, 2 glycine-conjugated bile acids, and 4 taurine-conjugated bile acids -

376

were simultaneously quantified in the liver of the control and EEA treated groups

377

(150 mg/kg) using our published method (Zhao et al., 2017). As shown in Fig. 9,

378

compared with the control group, the concentrations of 2 bile acids were significantly

379

increased, and one (CDCA) significantly decreased in mice liver. Among these bile

380

acids, bile acids such as TCA, CA and GCA exhibited the highest increases of 6.4-,

381

3.8-, and 5.7-fold, respectively. Most importantly, the taurine conjugated bile acid

382

TCA and free bile acid CA were both significantly elevated in the EEA-treated groups

383

(p < 0.01), indicating that, along with CDCA, bile acids including TCA and CA could 18

384

be considered as biomarkers of EEA induced liver injury.

385

4. Discussion

386

The EEA-associated hepatotoxicity has been well recognized in experimental

387

animals (Lin et al., 2015). However, its underlying mechanism of toxicity remains

388

largely unexplored to date. In this work, we utilized the integrated transcriptomics and

389

metabolomics approaches to identify the alterations of genes and metabolic profiles in

390

the livers of mice with EEA-induced liver injury. Mice developed hepatotoxicity

391

following 36 h administration of 150 mg/kg of EEA, which could be ascribed to the

392

down-regulation of key enzymes and disorder of BA metabolism in the liver.

393

Serum levels of ALT, AST and bilirubin are most commonly used in current

394

clinical practice, especially for acute hepatocellular injury (Whitfield et al., 1985;

395

Van-swelm et al., 2014). The hepatotoxicity induced by a single dose of EEA at 100

396

mg/kg reached a maximum at 36 h post treatment, with inflammatory cell infiltration

397

being observed (Lin et al., 2015). Correlating well with this evidence, our data

398

showed that the levels of ALT and AST were observed with the elevation in serum

399

and confirmed by inflammatory cell infiltration and focal necrosis in the liver of mice

400

given EEA at 150 mg/kg. Remarkably, we found that TBIL and DBIL levels were also

401

sensitive biomarkers, signifying the mechanism of EEA-induced liver injury. More

402

importantly, the serum biochemical parameters showed significant elevation in the

403

levels of ALP, indicating that the administration of EEA might influence the BAs

404

metabolism of the liver (Qu et al., 2017, Fuchs et al., 2017).

19

405

The liver is a multifunctional organ that is involved in various enzymatic

406

metabolic activities. Therefore, damage to this important organ by a hepatotoxic agent

407

will lead to a disturbance in the body metabolism (Ramadori et al., 2015; McEuen et

408

al., 2017). At 36 h after EEA (150 mg/kg) treatment, the expression of 625 genes

409

involved in the metabolic pathways was found to be significantly regulated. In

410

addition, drug metabolism cytochrome P450 and retinol metabolism also showed

411

significant change. Cytochrome P450 3A4 had been demonstrated to play critical

412

roles in EEA transformation to the corresponding cis-enedial intermediate, which

413

triggered the EEA-involved hepatotoxicity (Lin et al., 2016). The integrated analysis

414

results showed that the pathway “Drug metabolism – cytochrome P450” and

415

“Metabolism of xenobiotics by cytochrome P450” (Fig. 7) were found to be the

416

significant changed pathway in the model. Additionally, Fig. 6a shows glutathione

417

metabolism is significant but coverage level is not high, which may result from the

418

narrow detecting range provided by GC-MS method. This indicated that the metabolic

419

activation mediated by cytochromes P450 might be the triggering factors leading to

420

the development of EEA-induced liver injury.

421

Previous study showed that the DBT-induced hepatotoxicity had pronounced

422

impacts on the metabolism of amino acids (Zhao et al., 2017). Similarly, the results

423

from transcriptomics and metabonomics analyses (L-alanine, L-isoleucine, L-proline,

424

L-phenylalanine, and L-tyrosine) in our study supported this view that the metabolism

425

of amino acids played an important role in EEA-induced liver injury. Specifically, the

426

most notable changes were observed in taurine and hypotaurine metabolism. It should 20

427

be noticed that, compared with the control group, taurine was altered in the liver and

428

serum in response to EEA, while its content was increased in the serum and decreased

429

in the liver. Many studies have demonstrated that taurine was maintained in

430

abundance in the liver by both endogenous biosynthesis and exogenous transport,

431

though it decreased in liver diseases (Penttila et al., 1990; Matsuzaki et al., 1993;

432

Miyazaki and Matsuzaki, 2014). In addition, the most established role of taurine was

433

its conjugation with bile acids for excretion into bile (Danielsson, 1990). Therefore,

434

EEA-induced liver injuries might be strongly related to the reduction of taurine and

435

the disorder of BAs in the liver. The TCA cycle was an important hub of the

436

metabolism of carbohydrates, fats, and proteins, while L-malic acid, citric acid and

437

oxaloacetic acid were the dominant products of the TCA cycle (Vuoristo et al., 2016;

438

Zhang et al., 2016). As shown in Fig.5, L-malic acid and citric acid levels were

439

upgraded in EEA-treated groups, implying that there exists an imbalance with the

440

TCA cycle. Through further analysis, it was determined that TCA cycle functioned as

441

a bridge among the other disturbed metabolic pathways. Purine and pyrimidine

442

metabolisms might be the novel metabolic pathways for EEA-induced hepatotoxicity,

443

which was in agreement with our earlier work (Zhao et al., 2017). Taken in

444

combination, these results indicate that the EEA-induced liver injury might be

445

attributable in part ascribed to the imbalance of energy metabolism and metabolism of

446

amino acids.

447

Bile acid metabolism is referred to synthesis, transport and excretion (Halilbasic

448

et al., 2013). On one hand, the classical biosynthetic pathway (known as the neutral 21

449

BA biosynthetic pathway) is the primary pathway of BA biosynthesis. The present

450

RNA-Seq analysis showed that the expression of CYP7A1 (involved in BAs synthesis

451

from cholesterol) was significantly decreased, resulting in the reduction of BAs

452

biosynthesis (Russell, 2003). On the other hand, down-regulation was observed in the

453

expression of several important BAs transporters that joined in the hepatocellular

454

uptake: Na/taurocholate co-transporting polypeptide (NTCP/SLC10A1) and excretion

455

of BAs: bile salt export pump (BSEP), and the multidrug resistance protein 3 (MRP3)

456

(Soroka et al., 2014; Lam et al., 2010; Hirohashi et al., 2000). In general, we believed

457

that the metabolic balance of BAs was disturbed, thereby resulting in liver injury.

458

Thus, together with the protein analysis by western blotting analysis (Fig.8), these

459

results suggested that the imbalance of BAs metabolism might be responsible for

460

EEA-induced liver injury.

461

In summary, the integrative analysis of the gene expression and metabolites

462

levels changes following EEA exposure provide valuable information concerning the

463

hepatotoxic mechanism of action in different biological samples. In the process of 36

464

h administration of EEA (150 mg/kg), we found that the metabolic activation

465

mediated by cytochromes P450 might be the crucial steps in EEA-induced

466

hepatotoxicity, and the imbalance of energy metabolism, the metabolism of amino

467

acids and purine and pyrimidine metabolisms might also lead to the EEA-triggered

468

hepatic damage. This study suggested that the balance of BAs synthesis, uptake and

469

excretion was disturbed, the integrated effect on BAs metabolism resulting in liver

470

injury, and BAs including TCA and CA along with CDCA could be considered as 22

471

biomarkers of EEA-induced liver injury. The present findings will provide useful

472

information for further studies to examining the mechanism of EEA-induced

473

hepatotoxicity.

474

Acknowledgments

475

This work was supported by the National Natural Science Foundation of China

476

(No. 81773993) and the Project Funded by the Priority Academic Program

477

Development (PAPD) of Jiangsu Higher Education Institutions.

478

479

Conflicts of interest

480

The authors declare no conflicts of interest.

481

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647

31

648

Figure captions

649

Fig. 1 Summary figure representing the experimental design, methods and tools

650

applied to investigate EEA-induced hepatotoxicity in mice using the integrated

651

transcriptomic and metabolomics method. EEA: 8-epidiosbulbin E acetate.

652 653

Fig. 2 Typical liver histopathology (A: control group; B: EEA-treated group) and

654

biochemical parameters (C-G, ALT/AST/TBIL/DBIL/ALP activities) in mice 36 h

655

following i.g. administration of EEA at 0, 30, or 150 mg/kg. Results of quantitative

656

analysis values are expressed as mean ± SD (n = 6). Significant differences from the

657

value of control group with the administration of EEA were noted (*p < 0.05, **p <

658

0.01).

659 660

Fig. 3 GC-TOF MS profiles of serum samples in EEA (150 mg/kg) and control

661

groups. Principal component analysis (PCA) model (A) and the pattern recognition of

662

orthogonal partial least-squares-discriminate analysis (OPLS-DA) model (B/C). The

663

green circle represents control group, the blue circle represents EEA-treated group,

664

the red circle represents quality control（QC） group, respectively.

665 666

Fig. 4 GC-TOF MS profiles of liver tissue samples in EEA (150 mg/kg) and control

667

groups. PCA model (A) and the pattern recognition of OPLS-DA model (B/C).

668 669

Fig. 5 Heat map visualization of differentially abundant metabolites in serum (A) and 32

670

liver tissue (B) samples of EEA (150 mg/kg)-administered and control groups, Colors

671

from highest (red) to lowest (blue) represent metabolite expression values in different

672

groups.

673 674

Fig. 6 Analysis of metabolic disorders in serum (A) and liver tissue (B) in EEA (150

675

mg/kg)-treated groups and control groups using MetaboAnalyst 4.0. Bubble size and

676

color show the significance of path arrangement. The lighter and smaller bubbles

677

represent least affected pathways, whereas the larger and darker bubbles represent the

678

more markedly affected pathways.

679 680

Fig. 7 A summary of the result from the integrated pathway analysis module of

681

transcriptome and metabolome in EEA (150 mg/kg)-treated mice. The stacked bars

682

show the accumulated contributions from enrichment and topology analysis.

683 684

Fig. 8 Western verification results of differentially expressed genes (FN1, UGT1A1,

685

CYP1B1, CYP1A1, CYP2E1, CYP8B1, CYP7A1, BAAT, NTCP, BSEP and MRP3)

686

in the livers of mice treated with EEA at 30, or 150 mg/kg. β-actin level was used as

687

the internal reference. Vehicle: control group, EEA-30: EEA (30 mg/kg)-treated group,

688

EEA-150: EEA (150 mg/kg)-treated group.

689 690

Fig. 9 Alterations of the BAs concentrations in response to EEA (150 mg/kg)

691

consumption. The data are expressed as the mean ± SD (n = 6). Significant 33

692

differences from the value of control group with the administration of EEA were

693

indicated (*p < 0.05, **p < 0.01). Vehicle: control group, EEA-150: EEA (150

694

mg/kg)-treated group.

695

34

696

Table 1 The quantitative PCR primers of candidate genes. Number

Gene name

1

CYP7A1

2

BAAT

3

FH1

4

ABCC2

5

SlCO1A4

6

CYP2E1

7

ADA

8

IDH2

9

UGT1A1

10

CYP3A25

Primer sequence S: TTCATCACAAACTCCCTGTCATAC A: TTCCATCACTTGGGTCTATGCT S: ATGAATAGCCCCTACCAAATCC A: TCCACCAGCACCTCCAAACA S: AGATTGGAGGTGCTACGGAACG A: TCCAGTCTGCCAAACCACCA S: CATTGGCTTCGTGAAAGACCCT A: AATCGTGTACTGCCTCCTAGCC S: GGGTTGCCTGCTGCTCTAAGA A: TTCCGTTCTCCATCATTCTGCA S: AGGCTGTCAAGGAGGTGCTAC A: GCACAGCCAATCAGAAAGGTAG S: CAGACACCCGCATTCAACAA A: TGTCCATGCCGATAATGTTGC S: ACAGTCACCCGCCATTACCG A: TCCAGCGTCTGTGCAAACCT S: ACGCTGGGAGGCTGTTAGT A: CCGTCCAAGTTCCACCAAAG S: GGAGGCCTGAACTGCTAAAG A: GTAGTTGAAAATGGTGCCAAGTAAC

697

35

Highlights: An integrated transcriptomic/metabolomics method for screening EEA hepatotoxicity Purine and pyrimidine metabolisms might be the novel metabolic pathways for EEA-induced hepatotoxicity Imbalance of bile acid metabolism might be responsible for EEA-induced hepatotoxicity TCA and CA along with CDCA could be considered as biomarkers

Declaration of interests ☐ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

The authors declare that there is no conflict of interests regarding the publication of this article.